
"""simple docstring"""



import os
from datetime import datetime as dt

from github import Github


a       :						Any       		=		[
    '''good first issue''',
    '''good second issue''',
    '''good difficult issue''',
    '''enhancement''',
    '''new pipeline/model''',
    '''new scheduler''',
    '''wip''',
]


def 			_UpperCamelCase						(    )     ->	Union[str, Any]:





    """simple docstring"""

    _UpperCAmelCase        = Github(os.environ["""GITHUB_TOKEN"""]   )
    _UpperCAmelCase        = g.get_repo("""huggingface/diffusers"""   )
    _UpperCAmelCase        = repo.get_issues(state="""open"""   )

    for issue in open_issues:
        _UpperCAmelCase        = sorted(issue.get_comments()       ,   key=lambda _A   : i.created_at       ,   reverse=_A   )
        _UpperCAmelCase        = comments[0] if len(_A   ) > 0 else None
        if (
            last_comment is not None
            and last_comment.user.login == "github-actions[bot]"
            and (dt.utcnow() - issue.updated_at).days > 7
            and (dt.utcnow() - issue.created_at).days >= 3_0
            and not any(label.name.lower() in LABELS_TO_EXEMPT for label in issue.get_labels()   )
        ):
            # Closes the issue after 7 days of inactivity since the Stalebot notification.
            issue.edit(state="""closed"""   )
        elif (
            "stale" in issue.get_labels()
            and last_comment is not None
            and last_comment.user.login != "github-actions[bot]"
        ):
            # Opens the issue if someone other than Stalebot commented.
            issue.edit(state="""open"""   )
            issue.remove_from_labels("""stale"""   )
        elif (
            (dt.utcnow() - issue.updated_at).days > 2_3
            and (dt.utcnow() - issue.created_at).days >= 3_0
            and not any(label.name.lower() in LABELS_TO_EXEMPT for label in issue.get_labels()   )
        ):
            # Post a Stalebot notification after 23 days of inactivity.
            issue.create_comment(
                """This issue has been automatically marked as stale because it has not had """
                """recent activity. If you think this still needs to be addressed """
                """please comment on this thread.\n\nPlease note that issues that do not follow the """
                """[contributing guidelines](https://github.com/huggingface/diffusers/blob/main/CONTRIBUTING.md) """
                """are likely to be ignored."""   )
            issue.add_to_labels("""stale"""   )


if __name__ == "__main__":
 main()

"""simple docstring"""



import os
from shutil import copyfile
from typing import List, Optional, Tuple

from tokenizers import processors

from ...tokenization_utils import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
 from .tokenization_mbart import MBartTokenizer
else:
 a       :						Optional[Any]       		=		None


a       :						str       		=		logging.get_logger(__name__)


a       :						str       		=		{'''vocab_file''': '''sentencepiece.bpe.model''', '''tokenizer_file''': '''tokenizer.json'''}

a       :						str       		=		{
    '''vocab_file''': {
        '''facebook/mbart-large-en-ro''': (
            '''https://huggingface.co/facebook/mbart-large-en-ro/resolve/main/sentencepiece.bpe.model'''
        ),
        '''facebook/mbart-large-cc25''': (
            '''https://huggingface.co/facebook/mbart-large-cc25/resolve/main/sentencepiece.bpe.model'''
        ),
    },
    '''tokenizer_file''': {
        '''facebook/mbart-large-en-ro''': '''https://huggingface.co/facebook/mbart-large-en-ro/resolve/main/tokenizer.json''',
        '''facebook/mbart-large-cc25''': '''https://huggingface.co/facebook/mbart-large-cc25/resolve/main/tokenizer.json''',
    },
}

a       :						List[str]       		=		{
    '''facebook/mbart-large-en-ro''': 1_0_2_4,
    '''facebook/mbart-large-cc25''': 1_0_2_4,
}

# fmt: off
a       :						Optional[int]       		=		['''ar_AR''', '''cs_CZ''', '''de_DE''', '''en_XX''', '''es_XX''', '''et_EE''', '''fi_FI''', '''fr_XX''', '''gu_IN''', '''hi_IN''', '''it_IT''', '''ja_XX''', '''kk_KZ''', '''ko_KR''', '''lt_LT''', '''lv_LV''', '''my_MM''', '''ne_NP''', '''nl_XX''', '''ro_RO''', '''ru_RU''', '''si_LK''', '''tr_TR''', '''vi_VN''', '''zh_CN''']




class 		a_    (			_UpperCAmelCase						):
    a   :					Optional[int]			     =					VOCAB_FILES_NAMES
    a   :					List[Any]			     =					PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
    a   :					Optional[Any]			     =					PRETRAINED_VOCAB_FILES_MAP
    a   :					Optional[int]			     =					['input_ids', 'attention_mask']
    a   :					str			     =					MBartTokenizer

    a   :					List[int]			     =					[]
    a   :					List[int]			     =					[]







    def __init__(      self      :							str  ,       __UpperCamelCase      :							List[str]=None  ,       __UpperCamelCase      :							List[Any]=None  ,       __UpperCamelCase      :							Dict="<s>"  ,       __UpperCamelCase      :							int="</s>"  ,       __UpperCamelCase      :							str="</s>"  ,       __UpperCamelCase      :							Union[str, Any]="<s>"  ,       __UpperCamelCase      :							Any="<unk>"  ,       __UpperCamelCase      :							Any="<pad>"  ,       __UpperCamelCase      :							int="<mask>"  ,       __UpperCamelCase      :							Any=None  ,       __UpperCamelCase      :							Optional[Any]=None  ,       __UpperCamelCase      :							Optional[Any]=None  ,       **__UpperCamelCase      :							Optional[int]  ,       )		->Union[str, Any]:






        '''simple docstring'''






        _UpperCAmelCase        = AddedToken(__UpperCamelCase  ,       lstrip=__UpperCamelCase  ,       rstrip=__UpperCamelCase  ) if isinstance(__UpperCamelCase  ,       __UpperCamelCase  ) else mask_token

        super().__init__(
            vocab_file=__UpperCamelCase  ,       tokenizer_file=__UpperCamelCase  ,       bos_token=__UpperCamelCase  ,       eos_token=__UpperCamelCase  ,       sep_token=__UpperCamelCase  ,       cls_token=__UpperCamelCase  ,       unk_token=__UpperCamelCase  ,       pad_token=__UpperCamelCase  ,       mask_token=__UpperCamelCase  ,       src_lang=__UpperCamelCase  ,       tgt_lang=__UpperCamelCase  ,       additional_special_tokens=__UpperCamelCase  ,       **__UpperCamelCase  ,       )

        _UpperCAmelCase        = vocab_file
        _UpperCAmelCase        = False if not self.vocab_file else True

        _UpperCAmelCase        = FAIRSEQ_LANGUAGE_CODES.copy()

        if additional_special_tokens is not None:
            # Only add those special tokens if they are not already there.
            _additional_special_tokens.extend(
                [t for t in additional_special_tokens if t not in _additional_special_tokens]  )

        self.add_special_tokens({"""additional_special_tokens""": _additional_special_tokens}  )
        _UpperCAmelCase        = {
            lang_code: self.convert_tokens_to_ids(__UpperCamelCase  ) for lang_code in FAIRSEQ_LANGUAGE_CODES
        }

        _UpperCAmelCase        = src_lang if src_lang is not None else """en_XX"""
        _UpperCAmelCase        = self.convert_tokens_to_ids(self._src_lang  )
        _UpperCAmelCase        = tgt_lang
        self.set_src_lang_special_tokens(self._src_lang  )







    @property
    def   _snake_case       (      self      :							Optional[Any]  )		->str:






        '''simple docstring'''






        return self._src_lang







    @src_lang.setter
    def   _snake_case       (      self      :							int  ,       __UpperCamelCase      :							str  )		->None:






        '''simple docstring'''






        _UpperCAmelCase        = new_src_lang
        self.set_src_lang_special_tokens(self._src_lang  )







    def   _snake_case       (      self      :							str  ,       __UpperCamelCase      :							List[int]  ,       __UpperCamelCase      :							Optional[List[int]] = None  )		->List[int]:






        '''simple docstring'''






        if token_ids_a is None:
            return self.prefix_tokens + token_ids_a + self.suffix_tokens
        # We don't expect to process pairs, but leave the pair logic for API consistency
        return self.prefix_tokens + token_ids_a + token_ids_a + self.suffix_tokens







    def   _snake_case       (      self      :							Union[str, Any]  ,       __UpperCamelCase      :							List[int]  ,       __UpperCamelCase      :							Optional[List[int]] = None  )		->List[int]:






        '''simple docstring'''






        _UpperCAmelCase        = [self.sep_token_id]
        _UpperCAmelCase        = [self.cls_token_id]

        if token_ids_a is None:
            return len(cls + token_ids_a + sep  ) * [0]
        return len(cls + token_ids_a + sep + sep + token_ids_a + sep  ) * [0]







    def   _snake_case       (      self      :							Dict  ,       __UpperCamelCase      :							int  ,       __UpperCamelCase      :							str  ,       __UpperCamelCase      :							Optional[str]  ,       __UpperCamelCase      :							Optional[str]  ,       **__UpperCamelCase      :							Any  )		->Dict:






        '''simple docstring'''






        if src_lang is None or tgt_lang is None:
            raise ValueError("""Translation requires a `src_lang` and a `tgt_lang` for this model"""  )
        _UpperCAmelCase        = src_lang
        _UpperCAmelCase        = self(__UpperCamelCase  ,       add_special_tokens=__UpperCamelCase  ,       return_tensors=__UpperCamelCase  ,       **__UpperCamelCase  )
        _UpperCAmelCase        = self.convert_tokens_to_ids(__UpperCamelCase  )
        _UpperCAmelCase        = tgt_lang_id
        return inputs







    def   _snake_case       (      self      :							Tuple  ,       __UpperCamelCase      :							List[str]  ,       __UpperCamelCase      :							str = "en_XX"  ,       __UpperCamelCase      :							Optional[List[str]] = None  ,       __UpperCamelCase      :							str = "ro_RO"  ,       **__UpperCamelCase      :							Union[str, Any]  ,       )		->BatchEncoding:






        '''simple docstring'''






        _UpperCAmelCase        = src_lang
        _UpperCAmelCase        = tgt_lang
        return super().prepare_seqaseq_batch(__UpperCamelCase  ,       __UpperCamelCase  ,       **__UpperCamelCase  )







    def   _snake_case       (      self      :							Union[str, Any]  )		->int:






        '''simple docstring'''






        return self.set_src_lang_special_tokens(self.src_lang  )







    def   _snake_case       (      self      :							Union[str, Any]  )		->Tuple:






        '''simple docstring'''






        return self.set_tgt_lang_special_tokens(self.tgt_lang  )







    def   _snake_case       (      self      :							Union[str, Any]  ,       __UpperCamelCase      :							Dict  )		->None:






        '''simple docstring'''






        _UpperCAmelCase        = self.convert_tokens_to_ids(__UpperCamelCase  )
        _UpperCAmelCase        = []
        _UpperCAmelCase        = [self.eos_token_id, self.cur_lang_code]

        _UpperCAmelCase        = self.convert_ids_to_tokens(self.prefix_tokens  )
        _UpperCAmelCase        = self.convert_ids_to_tokens(self.suffix_tokens  )

        _UpperCAmelCase        = processors.TemplateProcessing(
            single=prefix_tokens_str + ["""$A"""] + suffix_tokens_str  ,       pair=prefix_tokens_str + ["""$A""", """$B"""] + suffix_tokens_str  ,       special_tokens=list(zip(prefix_tokens_str + suffix_tokens_str  ,       self.prefix_tokens + self.suffix_tokens  )  )  ,       )







    def   _snake_case       (      self      :							List[str]  ,       __UpperCamelCase      :							str  )		->None:






        '''simple docstring'''






        _UpperCAmelCase        = self.convert_tokens_to_ids(__UpperCamelCase  )
        _UpperCAmelCase        = []
        _UpperCAmelCase        = [self.eos_token_id, self.cur_lang_code]

        _UpperCAmelCase        = self.convert_ids_to_tokens(self.prefix_tokens  )
        _UpperCAmelCase        = self.convert_ids_to_tokens(self.suffix_tokens  )

        _UpperCAmelCase        = processors.TemplateProcessing(
            single=prefix_tokens_str + ["""$A"""] + suffix_tokens_str  ,       pair=prefix_tokens_str + ["""$A""", """$B"""] + suffix_tokens_str  ,       special_tokens=list(zip(prefix_tokens_str + suffix_tokens_str  ,       self.prefix_tokens + self.suffix_tokens  )  )  ,       )







    def   _snake_case       (      self      :							List[Any]  ,       __UpperCamelCase      :							str  ,       __UpperCamelCase      :							Optional[str] = None  )		->Tuple[str]:






        '''simple docstring'''






        if not self.can_save_slow_tokenizer:
            raise ValueError(
                """Your fast tokenizer does not have the necessary information to save the vocabulary for a slow """
                """tokenizer."""  )

        if not os.path.isdir(__UpperCamelCase  ):
            logger.error(f"""Vocabulary path ({save_directory}) should be a directory."""  )
            return
        _UpperCAmelCase        = os.path.join(
            __UpperCamelCase  ,       (filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]  )

        if os.path.abspath(self.vocab_file  ) != os.path.abspath(__UpperCamelCase  ):
            copyfile(self.vocab_file  ,       __UpperCamelCase  )

        return (out_vocab_file,)